Summary

This repository provides a comprehensive set of "skills" designed to equip AI coding agents with expert knowledge for common bioinformatics tasks. Targeting users from undergraduates to PhD researchers, it aims to enable AI agents to generate correct, idiomatic code for diverse workflows, ranging from basic sequence manipulation to advanced analyses like single-cell RNA-seq and population genetics, thereby accelerating research and learning.

How It Works

The project organizes bioinformatics expertise into structured "skills" (SKILL.md files) that guide AI coding agents such as Claude Code, OpenAI Codex, Google Gemini, and OpenClaw. Each skill encapsulates code patterns, best practices, and illustrative examples tailored for specific bioinformatics tasks. This approach standardizes and codifies domain knowledge, allowing AI agents to produce reliable and efficient code for complex biological data analysis pipelines.

Quick Start & Requirements

Installation involves cloning the repository and running agent-specific setup scripts (e.g., ./install-claude.sh). Key prerequisites include Python 3.9+, several Python libraries (biopython, pysam, anndata, etc.), R/Bioconductor packages (for advanced analyses), and a wide array of command-line tools (e.g., samtools, bcftools, STAR, MACS3) installable via package managers (brew, apt) or Conda. Selective installation by category is supported.

Highlighted Details

• Vast Skill Library: Offers 425 skills across 62 distinct bioinformatics categories, covering nearly every aspect of the field.
• Multi-Agent Compatibility: Designed for seamless integration with popular AI coding assistants like Claude Code, OpenAI Codex, Google Gemini, and OpenClaw.
• End-to-End Workflow Support: Encompasses skills for sequence I/O, alignment, variant calling, differential expression, single-cell analysis, structural biology, proteomics, metagenomics, and complex workflows.
• Structured Expertise: Each skill provides actionable code patterns, best practices, and examples to ensure idiomatic and correct code generation by AI agents.

Maintenance & Community

Development guidelines and quality standards are detailed in CLAUDE.md. No specific community links (e.g., Discord, Slack) or explicit maintenance schedules were detailed in the provided README excerpt.

Licensing & Compatibility

The project is released under the permissive MIT License, which generally allows for commercial use and integration into closed-source projects without significant restrictions.

Limitations & Caveats

The primary utility is contingent on the effective integration and interpretation capabilities of the supported AI coding agents. The extensive list of prerequisites across Python, R, and numerous CLI tools necessitates a complex and potentially time-consuming environment setup, which could be a barrier to rapid adoption.